The Autonomous Embedded Systems Engineering program trains specialists capable of designing, developing, and integrating intelligent embedded systems into autonomous devices.

These systems are at the heart of current technological innovations in fields such as robotics, autonomous vehicles, Internet of Things (IoT), aerospace, healthcare, Industry 4.0, and defense.

An autonomous embedded system combines sensors, local computing power, artificial intelligence algorithms, and real-time decision-making mechanisms, all integrated into a constrained environment (space, energy, communication).

Training Objectives

• Acquire solid expertise in embedded systems: electronics, microcontrollers, real-time systems
• Develop advanced skills in control engineering, embedded AI, and signal processing
• Design reliable and optimized hardware/software architectures for embedded environments
• Integrate sensors, actuators, and communication technologies to make a system autonomous and interactive
• Ensure cybersecurity, safety, and resilience of critical systems

Skills Acquired

• Hardware and software design of an embedded system
• Development of embedded software for autonomous systems
• Implementation of AI algorithms in constrained environments
• Integration of sensors and actuators for real-time decision-making
• Management of energy, size, cost, and reliability constraints

Career Opportunities

Graduates can work in high-tech sectors, including:

• Autonomous and connected vehicles (automotive, rail, aerospace)
• Mobile and industrial robotics
• Smart IoT devices
• Aerospace, defense, and space
• Digital health and medical devices
• High-tech companies, startups, R&D centers

Accessible Professions:

• Embedded Systems Engineer
• Autonomous Robotics Engineer
• Embedded AI Developer (Edge AI Engineer)
• Embedded Software Architect
• Cyber-physical Systems Integrator

The Robotics and Autonomous System Design program trains professionals capable of designing, modeling, programming, and integrating intelligent robotic systems that can operate autonomously in dynamic, complex, and often unpredictable environments.

In a context of digital and industrial transformation (Industry 4.0), smart mobility, automated services, and robotic exploration, graduates play a key role in technological innovation.

Training Objectives

• Master the fundamentals of mobile and industrial robotics, including kinematics, dynamics, and robot control
• Design and develop intelligent autonomous systems, integrating sensors, actuators, and perception/decision algorithms
• Acquire skills in artificial intelligence, computer vision, machine learning, and trajectory planning
• Understand and implement robotic autonomy technologies: navigation, mapping, SLAM, human-machine interaction
• Work on multidisciplinary projects combining mechatronics, embedded systems, and advanced algorithms

Skills Acquired

• Design and modeling of autonomous robots
• Programming and integration of smart sensors
• Development of autonomy and embedded intelligence algorithms
• Solving complex problems in real environments
• Teamwork in multidisciplinary settings and robotics project management

Career Opportunities

Graduates can pursue positions in various technological sectors:

• Industrial and collaborative robotics (cobots)
• Autonomous vehicles (automotive, rail, aerospace)
• Robotic healthcare and rehabilitation
• Service robotics and smart logistics
• Advanced robotics R&D

The Navigation and Control of Autonomous Systems program trains experts capable of designing, developing, programming, testing, and piloting autonomous systems (air, land, sea, or underwater), commonly known as drones or unmanned systems (UAV, UGV, USV, UUV).

In a context of digital transformation and increasing automation, unmanned systems play a strategic role in diverse sectors such as aerospace, defense, precision agriculture, logistics, environmental monitoring, security, and space exploration.

Training Objectives

• Gain deep expertise in navigation, guidance, and control (NGC) of autonomous systems
• Develop skills in modeling, control engineering, robotics, signal processing, embedded AI, and sensor fusion
• Understand drone system architecture and operational constraints
• Learn to integrate sensors (GPS, IMU, LiDAR, cameras) and process data for autonomous navigation
• Design and test navigation and autopilot algorithms in simulated and real environments

Skills Acquired

• Understanding of inertial, satellite (GNSS) navigation, and sensor fusion techniques
• Dynamic and kinematic modeling of aerial, land, and marine unmanned systems
• Numerical simulation of trajectories and navigation scenarios
• Development of robust control laws for stabilization and autopilot
• Implementation of guidance, navigation, and control (GNC) algorithms
• Integration of onboard sensors: IMU, GPS/GNSS, LiDAR, cameras, radars
• Use of Kalman filters and advanced multi-sensor fusion methods
• Application of machine learning and deep learning for perception and decision-making
• Development of autonomous navigation architectures in complex or GPS-denied environments
• Management of collaborative missions (drone fleets, swarms)
• Real-time programming on FPGA, DSP, and microcontrollers
• Embedded system software development (C/C++, Python, ROS)
• Inter-system communication and cybersecurity for autonomous systems

Career Opportunities

Graduates can work in innovative companies or public institutions in roles such as:

• Drone navigation and control engineer
• Autonomous robotic systems designer
• Embedded software developer for UAV/UGV
• Mobile robotics or intelligent systems expert
• R&D engineer in aerospace, defense, transport, or agriculture